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$200K GIVEAWAY - CODING TRADING AUTOMATIONS | August 14 | Michele RossiY — Transcript

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0:00Here
0:03we are back. Let's give a few seconds to
0:07everyone to connect and we're going to
0:10start our our live stream. I mean, we're
0:13already live, but going to start talking
0:15about what we did and where we at today,
0:19plus a crazy giveaway that we're doing
0:24it this morning.
0:32If you speak English, you can stay in.
0:34Both of you can join and enjoy the 200k
0:39giveaway. I will talk about it in a few
0:42seconds.
0:47Nice.
0:49So,
0:51here we are. Hey people, can you hear
0:54me? Can you guys see my screen?
0:57Say hello in the chat.
1:00Let's go. Ready for giveaway. Nice. It
1:02It is going to be huge.
1:06There's going to be a huge giveaway. Let
1:08me chat. Then we start our our live
1:11stream and I'm going to tell you guys
1:14what we did, what we coded and how it is
1:18going because I connected it on a on a
1:22Thunder Pro two-step challenge account
1:26and you're going to see how the bot that
1:29we coded live together using codeex jbt
1:33claude whatever you're using is going.
1:40Yes. Start subscribing to the channel
1:42and leave some comments down below.
1:45Say hello if you can see my screen and
1:50hear me.
1:56Say hello. Hello.
1:58Say hello. Hello.
2:02Beautiful.
2:03Beautiful.
2:11Hello everyone. Hello.
2:14Hello Santiago. Hello Shan Fidari.
2:18Hello Wah.
2:25And while we are waiting for everyone to
2:29answer hello, what you're looking at is
2:32the actual bot that we coded. And you
2:36can see all the takerit and stop-loss
2:38that it took.
2:40Sorry, I'm in the wrong time frame. 5
2:43minute time frame.
2:46Pretty straightforward. just took couple
2:49of sells during the night, sell right
2:53here, buy right there during the London
2:55market and took profit
2:58and I'm going to talk about it
3:01in a second.
3:04Right. Okay. As always, before we begin,
3:08let me know
3:10uh where you're where you're connecting
3:12from. Make yourself comfortable because
3:16today we are closing the circle on a
3:21project that started several weeks ago
3:24with nothing more than a simple trading
3:29idea.
3:31Everybody heard about
3:35many are talking about it is not a new
3:38strategy but many people many traders
3:42many influencers are talking about the
3:45orb
3:47the opening range breakout strategy. It
3:51has thousands of variation thousands of
3:55way to play with it.
3:58And my question was very simple. So the
4:02strategy say say this. So it is very
4:06simple strategy. You can use it on
4:08NASDAQ, Dow Jones, S&P 500, stocks,
4:13whatever. You just need to test it
4:16properly. And you have thousands of
4:17variation. The the the easiest variation
4:20is this one. uh you wait for uh at the
4:24New York Stock Exchange
4:28open time, right? Right. When it opens,
4:33the bell is ringing. Right. You wait 15
4:39minutes, the first 15 minute. So you let
4:42the the first 15 minute candle form and
4:45you mark up the
4:48or high
4:50and the or low, opening range high and
4:53opening range low. Then you go down to
4:56the fiveinut chart and you wait for the
4:59price to break above or below. Let's say
5:01it breaks above and you have a candle
5:05closing above. That is your entry point
5:08for a buy.
5:11Again, this is the most basic version of
5:14the order. It has thousands of
5:17variation, right? This is your buy
5:19position. You're going to put your entry
5:22right here. Stop loss. You can put it on
5:25the or low and target a one to one
5:27risk-to-reward
5:29or one or two or you can put your stop
5:32loss into the midline, the 50% of the
5:35range. You can put it down below the
5:37previous swing low. You can put it down
5:38the candle. You can use the anchored
5:42VWAP and you can use it as a trailing
5:45stop-loss for example. There's thousands
5:48of variation, right? So we said can we
5:51code can we make this happen
5:54automatically in our chart so that we
5:57can have a proper back test so that we
6:00can optimize by choosing the the best
6:04filters without exaggerating without um
6:11without I mean
6:14overfeed the strategy
6:17right and So yes, this is basically what
6:22we did from an idea to $500
6:29away from phase one,
6:32right? Because I deployed the strategy
6:35on a uh two-step challenge founder pro
6:40account and you're going to see in a
6:42minute how it went.
6:45stay connected because during this live
6:48I'm going to go and give away
6:53200k worth
6:56in challenges from Founder Pro. So stay
6:59connected. The more you're active in the
7:02chat, the more like you leave, the more
7:05questions you make, the more likely it's
7:08going to be you to win the challenge. So
7:15stay connected, listen, watch, ask,
7:18interact, and during the call, I'm going
7:22to tell you guys how to participate to
7:25this giveaway. $200,000
7:28worth of prop for free, given away to
7:32you guys. Um,
7:35remember that as of right now, you have
7:39a 30%
7:41off. You can see up above right here,
7:4530% off on any challenge, on any instant
7:51funed account, on any futures prop by
7:54using the code live that you can see
7:57below right here. Use the code LIV live
8:01to get a 30% off. It is valid until this
8:06live streams end. So, use it now before
8:09it's too late. Now let's go back to our
8:13um to our theme. Um
8:17so at the beginning of this series we
8:19asked a very practical question. Can an
8:22ordinary trader like you or like me I'm
8:25not an ordinary I'm a professional
8:27trader but let's say I'm an ordinary
8:29trader. Can we take an idea, explain it
8:32in plain English, use chip, codeex,
8:37uh, cloud, any AI and transform it into
8:41code, test it, validate it, and
8:44eventually deploy it as a completely
8:47automated trading system. We did not
8:51want to answer that question with
8:53theory. We wanted to build something,
8:55test it, and then place it inside a real
8:57proper environment. And that is exactly
9:02what uh what we did right. Um we started
9:08with an opening breakout strategy. Then
9:12we transformed it
9:15um we transformed the strategy
9:19um into objective rules, right? We
9:24developed it with codec. We back tested
9:28it.
9:30We optimized it. We validated it with
9:33statistical simulation. And finally, we
9:35deployed it on a $50,000 Founder
9:38ProCassic challenge. Give me a second
9:40because my uh presentation is stuck.
9:46[music]
9:53um
9:56is stuck. Let me try to fix it.
10:06Okay, we're going to take it back in a
10:09minute. Um,
10:11so
10:13the bot has now been operating for 18
10:18days and at the time of this live
10:21session, it is approximately
10:24$500
10:26away from its target.
10:29You can see a screenshot. It is running
10:31inside of a of a um VPS. And these are
10:37the trades started July 15. Of course, I
10:43uh created it um
10:46before um before we started this session
10:49and I deployed it right right before. Um
10:53does this mean that the challenge is
10:55already passed? We are sitting at
10:57$53,483.
11:00As you can see, it has a very very high
11:03win rate. That's what we wanted. If you
11:06missed how I coded it, how I did it, go
11:08back to YouTube um channel of Funder
11:11Pro, the same you're watching right now,
11:13and you can find all the series. Those
11:15are four videos. Um does it mean that
11:19the next trade will definitely be
11:21profitable? Absolutely not. Does does it
11:24mean that everyone can buy a challenge
11:26today, install a random bot and expect
11:28the same result? Again, no. What it
11:31means is that the entire process we
11:34discussed was not simply an academic
11:37exercise. We took an idea from a
11:39conversation, converted into code and
11:41deployed it into a challenge
11:42environment. So today I'm going to recap
11:46the complete journey, explain what we
11:49learned and then show you how the
11:51account has behaved during these first
11:5418 days.
11:56Before we continue, I want to thank
11:59Funder Pro once again for supporting
12:01these educational sessions and
12:04importantly for allowing properly
12:07designed algorithm trading,
12:10right? Um
12:14just a quick disclaimer, everything you
12:16see today is educational trading results
12:19are never guaranteed. Historical
12:21performance does not predict the future
12:23and the accounts and capital offered in
12:26these programs operate in a simulated
12:29trading environment. With that said,
12:32let's begin with a question that may
12:34make a few people slightly
12:36uncomfortable.
12:38Is your favorite trading guru lying to
12:42you? Let me know what you think in the
12:44chat.
12:51reach out to me on Instagram. My name is
12:54Mikuel Rosio
12:59and we can talk about it.
13:06Yes. Do you think your favorite trading
13:10guru is lying to you?
13:13So the honest answer is that they might
13:16be but they also might not be. Let me
13:21explain what I mean because I'm not
13:23saying that every discretionary trade
13:26that is dishonest that are extremely
13:29capable traders who have spent many
13:33years studying the market through
13:35experience. They may recognize certain
13:38situations very quickly. they can look
13:41at a chart and notice uh something that
13:44a beginner would probably miss. That
13:48experience can be real and valuable. The
13:51problem begins when somebody claims to
13:54teach you a repeatable strategy but
13:57cannot explain what they're actually
13:59doing. Imagine asking a trader, why did
14:02you enter that trade? And the answer is
14:05the market looked strong. That may sound
14:09reasonable, but it does not really
14:11answer the question. What exactly made
14:13the market look strong? Was the price
14:17above a moving average? Had it broken
14:19the previous high? Was volume
14:21increasing? Was volatility expanding?
14:24Had the market rejected the support
14:27level? Was another correlated market
14:29moving in the same direction? If we
14:31cannot answer those questions, the
14:33market looked strong is not a rule. It's
14:35an interpretation. Now imagine asking
14:38where the stop loss should be placed and
14:40receiving the answer. It depends on the
14:43market. Fine. What does it depend on?
14:47The sides of the opening range, the
14:48volatility um behind the previous
14:51candle, behind the swing point, a fixed
14:53number of points away from the entry.
14:55Again, it depends maybe true, but unless
14:59we can explain what it depends on, we
15:01cannot test it. This is why coding a
15:04strategy is so useful. Even if you do
15:07not intend to trade automatically,
15:10coding forces you to answer the
15:13questions that discretionary explanation
15:16often avoids. A computer does not
15:20understand that NASDAQ looks ready to
15:22explode. It does not understand that
15:25gold feels savvy. It does not known that
15:27the candle looks beautiful. The computer
15:30needs a measurable instruction. For
15:33example, instead of saying buy the
15:35NASDAQ looks strong, we may say wait
15:38until the first 15 minutes of the New
15:41York session have created a range in a
15:43five minute candle closes above the high
15:46of the range. If the range is not larger
15:49than a defined maximum, if no position
15:52is already open and if the daily risk
15:55limit has not been reached, then open a
15:58long position. Now the computer
16:01understand more importantly now we
16:04understand. Do you guys agree?
16:09I hope so.
16:13Right. Let's go back to our presentation
16:15is now ready.
16:17Right.
16:23Uh so back at it. Um,
16:32we have taken an opinion
16:35and turned into a condition,
16:40[music]
16:43right? Um, this does not necessarily
16:46make the strategy profitable, but it
16:48makes the strategy testable. That
16:51distinction is extremely important. The
16:54first question is not does this strategy
16:56make money. The first question is what
16:58exactly is this strategy? Only after we
17:01define it, we can test wherever it has
17:05produced a positive result. You may hear
17:08traders talking about intuition,
17:10discretion or experience.
17:14Sometimes they are describing genuine
17:17pattern recognition. Sometimes however
17:20fear and excitement are simply wearing a
17:23professional suit. Let me give you a
17:26very simple example. Imagine that you
17:28have tested a strategy over
17:31300 trades,
17:33right?
17:35Uh you have tested a strategy for over
17:38300 trades.
17:41According to your rules, the next valid
17:44signal should be taken. However, your
17:47previous trade was a loss. You look at
17:49the new setup and suddenly notice five
17:52different reasons why you may not work.
17:55The candle is not perfect. The breakout
17:58is a little fast. The market seems
18:00nervous. Perhaps you should wait for a
18:04confirmation. You script you you skip
18:07the trade and of course it becomes a
18:10winner. The following day, another
18:12signals appear. This time you're
18:14frustrated. because you missed yesterday
18:16winners. So you enter before the
18:19confirmation is complete. That trade
18:22loses
18:24at the end of the week. You believe the
18:26strategy has failed. In reality, you
18:28never traded the strategy. You traded a
18:31different set of emotion
18:34every day. This is one of the many and
18:38of the main reasons automation can be so
18:41powerful. It is not powerful because a
18:44bot can predict the future. It cannot.
18:46It is powerful because a properly
18:49designed bot can execute the same
18:51decision process consistently.
18:55It does not become scared because the
18:57previous trade lost. It does not become
19:00overconfident because the previous three
19:02trades won. It does not wake up in a bad
19:04mood and it does not increases the risk
19:07because it wants to pass a challenge
19:09before the weekend. However, there is
19:11another side risk. If the logic is bad,
19:14the bot will execute bad logic
19:17perfectly. So, if you tell a bot to
19:19enter every time a candle turns green,
19:21it will follow that instruction with
19:24extraordinary discipline. That does not
19:27make it a good strategy. Automation does
19:30not create an edge. Automation executes
19:32the edge. If an edge exists, that is why
19:36our process did not begin with the bot.
19:38It began with the idea. So during the
19:41first lesson, we discussed
19:45uh the difference
19:48uh between a trading concept and a
19:50complete trading strategy. Many traders
19:53say I trade breakouts or I use support
19:56and resistance or I buy when liquidity
19:58is taken. Those statements describe a
20:02general idea but they do not describe
20:05yet a complete system.
20:07>> [clears throat]
20:07>> Let's use a practical example. Suppose I
20:10say I buy when price break the
20:13resistance. The first
20:16the first um question is which
20:20resistance? It is yesterday higher the
20:22AA session the highest price of the
20:24previous 20 candles or a level that I
20:27draw manually.
20:29Then we need to define the breakout. It
20:31is enough for price to touch one point
20:33above the resistance or must the candle
20:36close above it. Which candle in which
20:38time frame? Then we need to define the
20:40entry. Do the ent do we entry
20:43immediately after the close, wait for a
20:45retest or use a stop order. After that,
20:49where does the stop loss go? Where is
20:52the target? How much capital do we risk?
20:54What happens if a breakout occurs during
20:56important economic news? What happens if
20:58we already have another position open?
21:01Until those questions have answers, we
21:04do not have a strategy, we have a
21:06starting hypothesis for this project. We
21:10selected the opening range breakout. We
21:13already talked about it, right? And we
21:17have it. We signal it right here once
21:20again. Then we did not ask codeex
21:24um please create a profitable trading
21:27bot. That kind of prompt may sound uh
21:30exciting but is it is almost
21:33meaningless. Codex does not possess a
21:36secret guarantee strategy and no serious
21:39development process um
21:43should begin with a request for
21:44guaranteed profits. Instead we describe
21:47our exact rules. We explained the
21:49session, the range, the entry condition
21:52as we did previously in this code and
21:54the parameters we wanted to adjust code
21:57extend generated the first version of
21:59the strategy in pine script which
22:01allowed us to install it on trading view
22:04and see the rules see the rules of the
22:08of the code right
22:12right here by editor.
22:15Okay. Uh was the first version perfect?
22:18No. And that is normal in software
22:21development. The first version is rarely
22:24the final version. The purpose of the
22:25first version is to create something
22:27that we can inspect,
22:30right?
22:32Um
22:34for example, we noticed that the visual
22:36range did not behave correctly or other
22:39small issues and we fixed it with
22:42codeex,
22:44right? We check at the range, the
22:47entries, the stop losses and Codex can
22:50write and analyze code very quickly but
22:53it cannot replace our responsibility to
22:56verify the logic. Right? So think of
22:59Codex as an extremely fast development
23:02partner.
23:04Okay. Once the first table version was
23:07working, we had a baseline. At that
23:10point in our question chain, we were not
23:12longer asking whether the orb could be
23:14coded. We were asking whether this
23:16particular version of the orb made sense
23:19when tested over historical data. So
23:25we examined the results and began the
23:28optimization phase. Optimization is
23:31often misunderstood. It does not mean
23:33changing hundreds of parameters until we
23:37discover the most profitable historical
23:39combination. If we do that, we can
23:41easily create a beautiful back test uh
23:44that has simply memorized the past,
23:48right? The result may look impressive,
23:52but it probably does not describe a
23:56genuine market behavior. Um
24:04it may simply describe historical noise
24:07that is known as overfeeding.
24:11Overfeeding.
24:13Uh a way to understand it is to imagine
24:15a student who memorizes the answer of
24:18one examination without understanding
24:21the subject. If the same questions
24:23appear again and again in the same
24:25order, the st the student looks like a
24:28genius. Change the questions slightly
24:30and everything's
24:33falls apart. So a robust trading trading
24:37strategy should not depend of one
24:39magical and extremely precise
24:42combination.
24:44So we tested sensible variation. We
24:47compared different profit targets and we
24:50also included commission sleepage and
24:54executions and assumptions. That is
24:58extremely important
25:00because what the price shown on a chart
25:04is not always the exact price at which a
25:07live order will be filled. The spread
25:10may widen, the market may move between
25:12the signal and execution. A small
25:15commission may appear insignificant on
25:17one trade but it can become very
25:19significant over hundreds of trades. So
25:23a realistic back test should not be
25:25designed to impress us. It should be
25:28designed to ch to challenge the strategy
25:32right. Um
25:37so after optimization we move to
25:40validation and this is where the project
25:42became particularly relevant to a prop
25:45firm challenge because a traditional
25:47back test show us one historical
25:50sequence of trades. It tells us what
25:52happened when the winners and losers
25:54arrive in that particular order.
25:56However, a prop firm account can fail
25:58before the complete sequence has time to
26:01produce its final result. Right?
26:06Imagine a strategy wins 10 trades. Five
26:09trades win $1,000 each and five trades
26:12lose $500 each. At the end, the strategy
26:14has made $2,500.
26:18If the trades arrives in a in an
26:21alternative order, win loss, win loss,
26:24the journey may feel relatively
26:27comfortable. But now place the same five
26:30losing trades at the beginning. The
26:33final mathematical results is still
26:35positive if the account survives long
26:38enough, but the account may hit its
26:40maximum draw down before the first
26:42winner arrived. So the strategy has the
26:46same trades and the same average
26:49performance but the order has changed
26:51the outcome of the challenge. That is
26:53why we exported the individual trades
26:58and used codecs
27:00um to help us run a Monte Carlo style
27:03simulations. We created many
27:06statistically similar version of the
27:08trading journey. In simple term, we ask
27:10if the futures contain similar winners,
27:13losers, uh, and streaks, but they arrive
27:17in a different possible sequences, how
27:20often might the strategy pass phase one
27:23and phase two? How frequently might it
27:27violate a draw down limit? Those
27:30simulations do not predict the future.
27:32They they are estimates based on
27:34historical evidence we provide. So if
27:37the market changes significantly, the
27:39future distribution may be different.
27:42Nevertheless,
27:44this gives us a much more intelligent
27:46way to think about risk.
27:50Instead of asking only did the back step
27:52the back test make 10%. We started
27:55asking how often did the simulated
27:58strategy reach 10% before touching the
28:01loss limit. That is the question that
28:04matter in a challenge. So we also
28:08compare different risk levels,
28:11right?
28:13Um
28:15because the Fun Pro Classic Challenge
28:18has unlimited duration, speed does not
28:20need to be our main objective. If I have
28:24unlimited time, why should I force the
28:27bot to sprint towards the target? The
28:30goal is not to pass tomorrow. The goal
28:31is to reach the target without breaking
28:34the account rules. That is a very
28:36different mindset. So before I show you
28:40again the current challenge, we need to
28:42understand exactly how automation fits
28:45into Funder Pro. Funder Pro currently
28:48allows expert advisor and trading bots
28:50provided that they are used fairly and
28:53the trader owns the system and its code.
28:57That's why I did this course for you
29:00guys. The bot cannot exploit delays,
29:03prices, technical inefficiencies,
29:06platform vulnerabilities, or unfair
29:09latency.
29:10Right? So, you have to be fair. That's
29:13their rules.
29:16Right?
29:20This is why I keep repeating that you
29:23need to understand and own your system.
29:26You do not want a mysterious black box
29:29that you cannot explain. You want to
29:32know what is what the box is doing, why
29:35it is entering, and how it control
29:40um
29:41controls risk.
29:44So, the $50,000 classic challenge used
29:47for this project has a phase one profit
29:50target of 10%, which means five um
29:56$5,000.
29:58Phase two has a five uh% target. The
30:03maximum daily draw down is 5% and the
30:05maximum overall draw down is 10%. The
30:09duration is unlimited. So, how is it
30:12going? As I show you before, we're
30:14sitting at 3,483.
30:19So, I need an extra not 500, I
30:23misspelled 1,500
30:26around about to pass phase one. And as
30:31you can see, the strategy has not
30:33changed. It always take you can
30:35screenshot it and re give it a try and
30:39check on the trades.
30:42Stop loss, take profit, stop loss, take
30:44profit. Stop loss, take profit, take
30:46profit, take profit, take profit, take
30:47profit. Five in a row.
30:50Stop loss, stop loss. Two in a row. Then
30:53take profit. 1 2 3 4 5 6 7 take profit
30:58in a row. Then another stop loss. tend
31:00to take profit. We might need another
31:03six, seven trades to pass the challenge,
31:06maybe less
31:08phase one. And I'm going to keep you um
31:13uh showing you guys how it is going.
31:18And these results that you see has been
31:21produced completely
31:23automatically,
31:24right? So I didn't intervene.
31:28Uh the result is very encouraging but
31:32the experiment is still running and I I
31:35suggest you guys to go back rewatch the
31:38videos and find your trading strategy.
31:42Simple rule you explain
31:45you code with codeex with GPT with uh
31:49deepse whatever whatever you want to
31:51use. And if you want to learn how I do
31:55this, if you want help developing your
31:58own automated strategy or if you want a
32:01personalized learning path, I also offer
32:04a one-to-one calls. So reach out to me
32:07on my Instagram channel, Mikeros
32:11official. Send me a direct message and
32:15ask me more. Right? We're going to do it
32:19together. So, let's go to the giveaway.
32:23Let me open up the rules of the
32:25giveaway.
32:29Uh,
32:33right. Rules of the giveaway. Let me
32:36pick it up and then the session is over.
32:38Are you guys with me? Say hi in the chat
32:43if you're ready for the giveaway.
32:47Beautiful
32:53giveaway. We have five challenge account
32:56that we're giving away. The first place
32:58is a 100K. The second place is a 50K.
33:02Third place 25K. Fourth place 10K. Fifth
33:05place 10K. Leave an honest review of
33:10your Fund Pro experience on Google
33:13reviews. Then submit the review URL via
33:18the Google form that you find down below
33:21these videos.
33:24Again, we're giving away 200K in total,
33:29five account, 100K, 50K, 25K, 10K, and
33:3310K.
33:35To enter the giveaway, you must
33:37subscribe to this channel, leave a like,
33:40leave a comment, follow me on Instagram,
33:42Mikosi official, and leave a honest
33:46review of your Thunder Pro experience on
33:50Google reviews. You can go on Google
33:52reviews, leave the reviews and say, I
33:55this is an example. I really loved the
33:59live session of Mikuel.
34:02They gave me a lot of insight about
34:06trading automation and such whatever.
34:09Google, not Trustpilot, Google
34:14reviews and submit the review URL. So
34:18when you post the review, you copy and
34:21paste the your your
34:25review on the form that you find down
34:28below this video. Right? So again, use
34:33the code live. You have extra 30 minutes
34:35to use the code live to get the 30% off
34:38any challenge, instant or future
34:40account. Thank you guys for being here
34:42with me. I will keep you posted how on
34:44how the bot goes and have a great day.
34:48Bye.

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